基于遗传算法的LuGre轮胎模型参数辨识研究

Research on the Parameter Identification of LuGre Tire Model Based on Genetic Algorithms

LuGre轮胎模型是一种动态轮胎摩擦力模型,该模型能够精确描述轮胎摩擦环节的动态特性,但由其高度非线性使得参数辨识非常困难.针对LuGre轮胎模型,提出一种基于遗传算法的模型参数两步辨识方法.首先由PD控制辨识出静态参数;然后由PID控制辨识出动态参数.在每一步辨识中,均采用遗传算法作为优化工具,从而避免了采用拟和辨识方法中误差较大,试验条件难以控制的缺点.该算法仅仅使用轮胎转速数据,而转速传感器是汽车防滑刹车控制系统(ABS)的基本组成部分,因此该算法可以与ABS结合工作,低成本的实现LuGre轮胎模型参数辨识.

The LuGre tire model is an dynamic tire friction model which can accurately describe the dynamic characteristic, but because of its high nonlinearity, it is very difficult to identify the parameters of the model. A two-step method for the parameter identification of LuGre tire model based on genetic algorithms is presented in this paper. In the first step,four static parameters are estimated via PD control, and in the second step, two dynamic parameters are obtained by the PID control. In the two steps, genetic algorithmsare used to minimize the identification error, thus the great error problem existing in the fitting identification method can be avoided. The two-step method estimates parameter only using wheel angular velocity information. Since the wheel speed sensor is a basic component of normal anti-lock brake system （ABS）, The method proposed could be easily realized in low cost within the anti-lock brake system.